{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:44:27Z","timestamp":1785545067208,"version":"3.56.0"},"reference-count":116,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Digital health interventions (DHIs) are increasingly used to support antiretroviral therapy (ART) management among people living with HIV. However, existing systematic reviews have largely focused on single intervention types or limited outcomes, and few have integrated multiple DHI modalities across both behavioral and clinical end points. Additionally, previous evidence has rarely incorporated analytical approaches, such as prediction intervals (PIs) or trial sequential analysis (TSA), leaving uncertainty regarding the robustness and generalizability of findings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This systematic review aimed to evaluate the effectiveness of DHIs in improving ART-related outcomes among people living with HIV.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We systematically searched PubMed, Cochrane Library, Embase, and Web of Science for randomized controlled trials (RCTs) published up to February 29, 2026. Eligible studies included people living with HIV receiving ART and evaluated DHIs, such as SMS, mobile apps, phone calls, adherence monitoring devices, multimedia education, or multicomponent interventions. Outcomes included viral suppression, CD4\n                      <jats:sup>+<\/jats:sup>\n                      cell count, adherence, and retention. Random-effects meta-analyses were conducted using restricted maximum likelihood estimation with Hartung-Knapp-Sidik-Jonkman adjustment. Effect sizes were reported as risk ratios (RRs) or mean differences (MDs) with 95% CIs and 95% PIs. TSA was performed to assess the sufficiency of cumulative evidence. A frequentist network meta-analysis was conducted to compare the relative effectiveness of different DHIs.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 64 RCTs involving 22,286 participants were included. Compared with standard of care (SOC), DHIs improved subjective adherence (RR 1.13, 95% CI 1.04\u20101.23; 95% PI 0.82\u20101.57) and retention (RR 1.06, 95% CI 1.01\u20101.12; 95% PI 0.81\u20101.39). Viral suppression was modestly improved (RR 1.04, 95% CI 1.01\u20101.07; 95% PI 0.96\u20101.13), while no significant effect was observed for CD4\n                      <jats:sup>+<\/jats:sup>\n                      cell count and objective adherence. TSA indicated sufficient evidence for viral suppression and subjective adherence but inconclusive evidence for other outcomes. In the network meta-analysis, SMS, mobile apps, and multicomponent interventions demonstrated statistically significant benefits versus SOC; however, all PIs crossed the null. Although phone calls ranked highest by surface under the cumulative ranking curve (SUCRA), differences between interventions were not robust.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In contrast to previous systematic reviews that focused on single intervention types or limited outcomes, this systematic review provides a comprehensive synthesis of multiple outcomes across all types of DHIs, supporting their potential role as nonpharmacological strategies in HIV care. However, the wide 95% PI, together with a high risk of bias, small-study effects, and low to very low certainty of evidence based on GRADE (Grading of Recommendations Assessment, Development, and Evaluation), indicate substantial uncertainty regarding the true effects in future settings. Therefore, these findings should be interpreted with caution. These findings have important practical implications, as they may directly help inform the design of more targeted and context-specific digital interventions and highlight the need for further research to identify optimal implementation strategies in routine HIV care.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/81019","type":"journal-article","created":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T18:47:31Z","timestamp":1784832451000},"page":"e81019-e81019","source":"Crossref","is-referenced-by-count":0,"title":["Effectiveness of Digital Health Interventions for Improving Antiretroviral Therapy Outcomes in People With HIV: Meta-Analysis and Trial Sequential Analysis of Randomized Controlled Trials"],"prefix":"10.2196","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-3285-0347","authenticated-orcid":false,"given":"Pan","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0511-3365","authenticated-orcid":false,"given":"Jiahao","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8389-8463","authenticated-orcid":false,"given":"Xi","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4048-4380","authenticated-orcid":false,"given":"Yilin","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8350-2577","authenticated-orcid":false,"given":"Xuanyu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8812-7419","authenticated-orcid":false,"given":"Yuqing","family":"Xiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1135-7876","authenticated-orcid":false,"given":"Shuguang","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,7,23]]},"reference":[{"key":"R1","unstructured":"HIV data and statistics. 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